{"id":"W7130276766","doi":"","title":"DNA barcoding aids in generating a preliminary checklist of the lichens and allied fungi of Calvert Island, British Columbia: Results from the 2018 Hakai Terrestrial BioBlitz","year":2024,"lang":"","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Checklist; DNA barcoding; Lichen; Taxonomy (biology); Biodiversity","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001651337,0.001582835,0.001111034,0.007550864,0.002695078,0.00221721,0.002682297,0.00174928,0.02665293],"category_scores_gemma":[0.008637087,0.0008407019,0.0007185343,0.01047573,0.0006887107,0.0007026718,0.00278121,0.001974513,0.02558428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005719612,"about_ca_system_score_gemma":0.01878922,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8343437,"about_ca_topic_score_gemma":0.9251177,"domain_scores_codex":[0.998799,0.00009443766,0.0001063475,0.0002824161,0.0004002073,0.0003176438],"domain_scores_gemma":[0.9930981,0.0009515341,0.0004319707,0.0009154279,0.003946699,0.0006563566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001104687,0.00003183337,0.0104349,0.0008588133,0.00006077461,0.00006780797,0.0002563184,0.0004560527,0.0004818499,0.0004468774,0.9795343,0.007260027],"study_design_scores_gemma":[0.0002198701,0.00001203497,0.09345657,0.001147994,0.0001210386,0.00006032161,0.001047654,0.000987248,0.001029868,0.001191198,0.9006429,0.00008329552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009762906,0.00004788464,0.00007415273,0.00004186881,0.00001012712,0.00001538122,0.9980655,0.0001613853,0.0006073717],"genre_scores_gemma":[0.001671642,0.00005076023,0.0005039137,0.00002369594,0.000002587976,0.00009672892,0.9966459,0.00005624399,0.0009485608],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1656563,"threshold_uncertainty_score":0.3332638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329809331843349,"score_gpt":0.2803000550488564,"score_spread":0.2470019617304229,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}